How to use Bloom’s Taxonomy to create differentiated outcomes for your learners and why doing so can be useful, but is not necessarily a perfect answer

Creating Differentiated Outcomes

Once we have a learning objective, we have the focus of our lesson.

Next, we need some outcomes.

These are the things learners will be able to do to show they have met the learning objective.

Differentiated outcomes take account of the different starting points of our learners, as well as the likelihood that not everybody will make the same degree of progress in any particular lesson.

The common formulation is All/Most/Some.

This divides the class into three rough groups, not necessarily of equal size.

The ‘all’ outcome is the minimum everyone is expected to achieve.

The ‘more’ outcome is what most learners will access (or those who put in more effort) and the ‘some’ target is designed to meet the needs of the most able learners.

One of the problems with differentiated outcomes is that they can set a ceiling on learner achievement, labelling different groups as only being capable of getting to certain outcomes.

This is not what we want.

Three simple techniques can be employed to avoid this.

First, while we continue to use the all/most/some formulation, we make clear to learners that this is for guidance only and that it does not refer to specific groups in the class.

This implies that the top levels of progress are open to everyone and, therefore, that nobody’s efforts in pursuit of mastery will be wasted.

Second, we can get rid of the all/most/some language altogether and replace it with something different.

For example, some teachers like to use colours for different outcomes or, with younger learners, a series of related nouns.

Here, the aim is to maintain the difference between outcomes, as well as the sense of increasing difficulty, but to communicate this without a sense of exclusivity about who can achieve what.

Third, we can ensure our ‘all’ outcome is challenging in itself, with the ‘most’ and ‘some’ outcomes then being even more challenging.

This is a way to get round the idea that the outcomes are differentiated in accordance with expectations about inherent ability.

Instead, they are differentiated according to relative degrees of challenge – from challenging to very challenging.

My personal preference is for a combination of the first and third options.

This sees us twice reinforcing high expectations to learners.

First through the outcomes we set, then by communicating that these are potentially accessible to everyone in the class.

Start with Your Objective

When constructing your outcomes, begin with your objective.

Work back from there and ask yourself what learners will need to be able to do to successfully meet it.

This illustrates why challenging objectives are so important.

If they are too easy, the outcomes to which they give rise will not be sufficiently challenging.

When developing outcomes, use the taxonomy and focus on higher-order keywords.

For example, we might use analysis for our ‘all’ outcome, synthesis for our ‘most’ outcome and evaluation for our ‘some’ outcome.

Our goal then is for every learner to, at a minimum, reach the fourth level of the taxonomy, though we still aren’t placing any restrictions on any learner going beyond that.

For example:

LO: To assess the arguments for and against the use of proportional representation
All will be able to explain in detail at least three arguments for and three arguments against in a piece of individual writing about proportional representation.
Most will be able to create a piece of writing that is balanced, taking into account both points of view.
Some will be able to rank the arguments on both side as part of their writing and come to a critical conclusion as a result.

This example has its merits.

However, a clear limitation is that it suggests only those who reach the third outcome will be able to fully achieve the objective.

This is a little problematic as it relies on us communicating to learners that, although the outcomes are in the form All/Most/Some, the latter are still achievable by everyone in the class.

An alternative approach is to take the objective as the starting point, including the level of the taxonomy to which it refers, and to break this down into three levels of increasing complexity.

Here is an example:

LO: To assess the arguments for and against the use of proportional representation
All will be able to assess the arguments for and against the use of proportional representation, explaining which side they think is more persuasive and why.
Most will be able to critically assess the arguments, suggesting why a range of opinions exist, before giving their own perspective and supporting this with reasons, evidence and examples.
Some will be able to draw out the key concepts underpinning the arguments on each side and use this as the basis of a critical assessment of why different positions exist and whether these can be effectively reconciled.

The advantage of this approach is that each outcome sees the learning objective being met.

The level at which it is met increases on each occasion.

Those learners who hit the third objective will be working at a very high level indeed.

It works on the basis that within any level of the taxonomy, there are gradations of mastery.

We see that in the example.

For each successive outcome, the quality and depth of evaluation is increasing. Yet each outcome is still concerned with evaluation.

(Personally, I like this approach, and the level of challenge and high expectations it engenders.)

The disadvantage is that the outcomes have become slightly more cumbersome and, as a result, a little harder to communicate.

Life Isn’t Perfect

I don’t think there is a perfect solution to the problem.

Both approaches to constructing outcomes have their benefits, but neither is perfect.

The important thing to remember is that, whichever approach you choose, the outcomes should move up the taxonomy to ensure the pursuit of mastery remains integral to the lesson.

In addition, having made yourself aware of the potential drawbacks of your chosen approach, you can then look to mitigate these either by, in the first case, helping learners to see all the outcomes as accessible or, in the second case, carefully modelling and explaining the outcomes to aid learner understanding.

A final point to note is that there is a question as to whether learners need to know all the outcomes anyway.

Perhaps sharing a well-constructed learning objective, accompanied by a verbal explanation of what success will look like, is enough.

That’s for you to decide.